Predictive caching for content

ABSTRACT

Disclosed are various embodiments for predictive caching of content to facilitate instantaneous use of the content. If a user is likely to commence use of a content item through a client, and if the client has available resources to facilitate instantaneous use, the client is configured to predictively cache the content item before the user commences use. In doing so, the client may obtain metadata for the content item from a server. The client may then initialize various resources to facilitate instantaneous use of the content item by the client based at least in part on the metadata.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims priority to,co-pending U.S. Patent Application entitled “PREDICTIVE CACHING FORCONTENT,” filed on Nov. 30, 2015, and assigned application Ser. No.14/953,891, which is a continuation of, and claims priority to, U.S.Patent Application entitled “PREDICTIVE CACHING FOR CONTENT,” filed onAug. 23, 2012, and assigned application Ser. No. 13/592,752, whichissued as U.S. Pat. No. 9,215,269 on Dec. 15, 2015, and which areincorporated herein by reference in their entirety.

BACKGROUND

Network-based delivery of media content has largely supplanted otherforms of media content delivery, such as brick-and-mortar video salesand rental stores, mail-based video rental services, and so on. Insteadof traveling a few miles to a physical store or waiting days for a titleto arrive by mail, users may select media content titles to stream totheir devices over high-speed broadband connections. Consequently, usersare quickly growing accustomed to near-immediate delivery of mediacontent. Rising user expectations may lead to frustration when playbackdoes not begin immediately upon user selection of a media content title.

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the present disclosure can be better understood withreference to the following drawings. The components in the drawings arenot necessarily to scale, with emphasis instead being placed uponclearly illustrating the principles of the disclosure. Moreover, in thedrawings, like reference numerals designate corresponding partsthroughout the several views.

FIG. 1A is a drawing presenting one example of operation of a networkedenvironment according to various embodiments of the present disclosure.

FIG. 1B is a drawing presenting a detailed view of the networkedenvironment of FIG. 1A according to various embodiments of the presentdisclosure.

FIG. 2 is a flowchart illustrating one example of functionalityimplemented as portions of a predictive caching system executed in aclient in the networked environment of FIG. 1B according to variousembodiments of the present disclosure.

FIG. 3 is a flowchart illustrating one example of functionalityimplemented as portions of a content access application executed in aclient in the networked environment of FIG. 1B according to variousembodiments of the present disclosure.

FIG. 4 is a flowchart illustrating one example of functionalityimplemented as portions of a content server executed in a computingenvironment in the networked environment of FIG. 1B according to variousembodiments of the present disclosure.

FIG. 5 is a schematic block diagram that provides one exampleillustration of a computing environment employed in the networkedenvironment of FIGS. 1A and 1B according to various embodiments of thepresent disclosure.

DETAILED DESCRIPTION

The present disclosure relates to predictive caching for content itemssuch as, for example, movies, television programs, music, video clips,audio clips, applications, and so on. Such content is increasinglyoffered through network streaming or progressive download. If thenetwork connection of the user has bandwidth exceeding the bitrate ofthe content, the content can be played back or otherwise used while itis being downloaded or streamed. Despite having the network bandwidth tosupport streaming, users may still experience delay after initiallyselecting a content item for use. For example, playback may be delayedfor several seconds, leading to user frustration. This delay may be dueto the initial filling of buffers in the client with portions of thecontent item; launching and initializing various software and/orhardware components in the client to perform decryption, decoding, orother functions; or other causes.

Various embodiments of the present disclosure enable instantaneous, ornear instantaneous, playback of network-streamed or progressivelydownloaded content by predictively caching initial portions of contentitems that a user is likely to playback or use. The predictive cachingmay involve downloading initial portions of the content item in advance,downloading metadata including manifest files and decryption keys,decrypting the initial portions of the content items, performingconfiguration tasks, performing initialization tasks, and/or performingother tasks relating to preparing a content item for playback. Thepredictive cache may be maintained and updated according to availabledata storage, available network bandwidth, recommendations data,real-time user behavior data, and/or other factors.

With reference to FIG. 1A, shown is one example of operation for anetworked environment 100 according to various embodiments. Thenetworked environment 100 includes a computing environment 103 in datacommunication with one or more clients 106 via a network 109. The client106 is rendering a user interface 112 that allows a user to browsecontent items that are available for playback or use. A recommendation115 is rendered in the user interface 112 in this non-limiting example.The recommendation 115 recommends to the user a movie (“World of theGorillas”) that has been predictively cached in the client 106 forinstantaneous playback.

The client 106 includes a predictive cache 118 in memory that stores acontent item initial portion 121 and content item metadata 124 for eachpredictively cached content item. Through predictive caching, the client106 is configured to obtain the content item initial portion 121 and thecontent item metadata 124 from the computing environment 103 over thenetwork 109 before the user at the client 106 requests use or playbackof the content item. Further, the client 106 may initialize varioussoftware and/or hardware components based at least in part on thecontent item initial portion 121 and/or the content item metadata 124 inorder to provide an instantaneous use experience when the user selectsthe content item for use.

After the user requests use of the content item, the client 106 may thenbegin to obtain content item subsequent portions 127 in a content stream130 over the network 109 from the computing environment 103. Thus, asthe client 106 exhausts use of the content item initial portion 121, theclient 106 may seamlessly continue use of the content item subsequentportions 127. In the following discussion, a general description of thesystem and its components is provided, followed by a discussion of theoperation of the same.

Turning now to FIG. 1B, shown is a detailed view of the networkedenvironment 100 according to various embodiments. The networkedenvironment 100 includes the computing environment 103 in datacommunication with one or more clients 106 via the network 109. Thenetwork 109 includes, for example, the Internet, intranets, extranets,wide area networks (WANs), local area networks (LANs), wired networks,wireless networks, or other suitable networks, etc., or any combinationof two or more such networks.

The computing environment 103 may comprise, for example, a servercomputer or any other system providing computing capability.Alternatively, the computing environment 103 may employ a plurality ofcomputing devices that may be employed that are arranged, for example,in one or more server banks or computer banks or other arrangements.Such computing devices may be located in a single installation or may bedistributed among many different geographical locations. For example,the computing environment 103 may include a plurality of computingdevices that together may comprise a cloud computing resource, a gridcomputing resource, a content delivery network, and/or any otherdistributed computing arrangement. In some cases, the computingenvironment 103 may correspond to an elastic computing resource wherethe allotted capacity of processing, network, storage, or othercomputing-related resources may vary over time.

Various applications and/or other functionality may be executed in thecomputing environment 103 according to various embodiments. Also,various data is stored in a data store 133 that is accessible to thecomputing environment 103. The data store 133 may be representative of aplurality of data stores 133 as can be appreciated. The data stored inthe data store 133, for example, is associated with the operation of thevarious applications and/or functional entities described below.

The components executed on the computing environment 103, for example,include a recommendations engine 136, a content server 139, and otherapplications, services, processes, systems, engines, or functionalitynot discussed in detail herein. The recommendations engine 136 isexecuted to generate a list of recommended content for a user. To thisend, the recommendations engine 136 may analyze various behavioral datacollected regarding the user. The list of recommended contentcorresponds to content that the user is likely to playback or consume.The list may include relative priorities for the recommended content.The list may be sent to the client 106 over the network 109 asrecommendations data 142.

The content server 139 is executed to serve up content items andassociated data to users at clients 106. To this end, the content server139 is configured to send content data 145 to the client 106 via thenetwork 109. In addition, the content server 139 may generate and senduser interface data to the client 106 to facilitate user browsing,searching, and/or selection of content. Such user interface data maycorrespond to web page data, mobile application data, and/or other formsof user. Such user interface data may include hypertext markup language(HTML), extensible markup language (XML), cascading style sheets (CSS),and/or other data. In one embodiment, the content server 139 may senddirectives to the client 106 that instruct the client 106 topredictively cache preselected content items.

The data stored in the data store 133 includes, for example, useraccount data 148, a content library 151, and potentially other data. Thecontent library 151 includes data relating to content items that aremade available by the content server 139 for playback, download,viewing, lease, purchase, etc. Such content items may include, forexample, movies, television shows, music, music videos, video clips,audio clips, applications such as mobile applications, and so on. Thecontent library 151 may include content portions 153, metadata such asmanifests 155 and decryption keys 157, and/or other data.

Each of the content portions 153 may correspond to a distinct timesegment of the particular content item. In some cases, multiplealternative content portions 153 may be provided for time segments,e.g., both English and Spanish language audio tracks, different bitrateswith different encoding qualities, and so on. The content portions 153may include Moving Pictures Experts Group (MPEG) video data, H.264 data,Flash® media data, MPEG layer 3 (MP3) audio data, Dolby Digital® audiodata, Advanced Audio Coding (AAC) audio data, data for subtitles, etc.

The manifests 155 may describe, for example, how a particular contentitem is made up of various content portions 153. The manifest 155 mayinclude identifiers for content portions 153 that make up the contentitem along with sequence-specifying data so that the client 106 canobtain and render the content portions 153 in the correct order. Themanifest 155 may also identify various alternative content portions 153for a content item such as, for example, alternative languages,alternative bitrates, and other alternatives. In some cases, themanifest 155 may provide license-related information, including thelocation of the decryption keys 157.

The decryption keys 157 may be employed by the client 106 to decryptcontent portions 153 which are encrypted under digital rights management(DRM) technologies. A decryption key 157 may be sent along with thecontent portions 153 if the client 106 has rights to the correspondingcontent item. The rights to the corresponding content item may expire ata particular time, after a time period, upon a certain number of playsfor the content item, or at some other time. Thus, the decryption keys157 may be configured to expire in response to expiration of the rightsof the client 106 to the corresponding content item. In someembodiments, the decryption keys 157 may be referred to as “licenses”for the corresponding content items.

The user account data 148 may include various data associated with useraccounts with the content server 139. Such accounts may be explicitlyregistered and configured by users or may be created implicitly based onclient 106 interaction with the content server 139. The user accountdata 148 may include, for example, behavior history 160, real-timebehavior data 162, bandwidth history 164, content preferences 166, watchlists 168, recommended lists 170, subaccount data 172, content rights175, and other data. In addition, security credentials, contactinformation, payment instruments, and/or other user-related data may bestored in the user account data 148.

The behavior history 160 describes historical behavior of the userassociated with the user account. Such behavior may include a contentconsumption history describing which content items the user has viewed,downloaded, purchased, etc. In one example, the content consumptionhistory corresponds to a media consumption history indicating whichmedia content items the user has viewed, downloaded, purchased, etc.Such behavior may also include a browse history tracking network pagesor content the user has previously accessed, a search history trackingprevious search queries, subscription history, purchase and browsehistory for non-content items, and/or other forms of online behavior.

The real-time behavior data 162 may include data describing what theuser is currently doing, e.g., what content the user is currentlybrowsing, what search queries the user is currently executing, whatsearch results are being displayed to the user, etc. The real-timebehavior data 162 may be observed by the content server 139 or collectedfrom reports by the client 106. For example, the client 106 may beconfigured to report to the content server 139 that the user is hoveringa cursor over a description of a certain content item in a userinterface. In some embodiments, the real-time behavior data 162 may bemaintained in the client 106 rather than the computing environment 103.

The bandwidth history 164 profiles the network bandwidth available forthe user through the client 106. The bandwidth history 164 may beemployed to select from among multiple bitrates of content itemsautomatically for predictive caching. If the user employs multipleclients 106, multiple profiles may be created in the bandwidth history164. Also, multiple location-dependent profiles may be created forclients 106 that are mobile devices. As a non-limiting example, a usermay have third-generation (3G) cellular data access at an officelocation, but high-speed Wi-Fi data access at a home location, therebyresulting in multiple location-dependent bandwidth profiles for the sameclient 106 in the bandwidth history 164.

The content preferences 166 include various preferences inferred fromuser behavior or explicitly configured by users. Such preferences may berelating to media content quality (e.g., bitrate, codec, etc.), languagepreferences, subtitle preferences, closed captioning preferences,supplemental content preferences (e.g., relating to directors' oractors' commentaries, etc.), parental control preferences, and so on.The watch lists 168 may correspond to lists of content items in whichusers have explicitly indicated that they desire to consume the contentat some time in the future. The recommended lists 170 correspond tolists of recommended content items generated for each user by therecommendations engine 136.

The subaccount data 172 may be employed to describe preferences orbehaviors that differ across multiple users of a user account. Forinstance, a family may have a single user account but subaccounts foreach member of the family. Each user may explicitly log in to asubaccount, or the subaccount may be inferred based on time of day, dayof the week, identity or type of the client 106, location of the client106, and/or other factors. In some cases, one user may be associatedwith multiple subaccounts. Further, a subaccount may be associated withmultiple users. The subaccount data 172 may specify restrictions oncontent access in some cases. As a non-limiting example, a subaccountfor a child may be limited to access only child-friendly content fromapproved sources. In some cases, different subaccounts may be associatedwith different clients 106.

The content rights 175 may describe the rights to content which areassociated with the user account. For example, a user may have asubscription to certain content or all content available through thecontent server 139. Such a subscription may be for indefinite use of theaccessed content, time-limited use, device-limited use, and/or otherlicensing arrangements. Alternatively, a user may purchase or leasecontent on a per-content-item basis.

The client 106 is representative of a plurality of client devices thatmay be coupled to the network 109. The client 106 may comprise, forexample, a processor-based system such as a computer system. Such acomputer system may be embodied in the form of a desktop computer, alaptop computer, personal digital assistants, cellular telephones,smartphones, set-top boxes, music players, web pads, tablet computersystems, game consoles, electronic book readers, or other devices withlike capability. The client 106 may include a display 177. The display177 may comprise, for example, one or more devices such as liquidcrystal display (LCD) displays, gas plasma-based flat panel displays,organic light emitting diode (OLED) displays, LCD projectors, or othertypes of display devices, etc.

The client 106 may be configured to execute various applications such asa content access application 179, a predictive caching system 181,and/or other applications. The content access application 179 may beexecuted in the client 106, for example, to access and render contentitems from the computing environment 103 and/or other servers. Moreover,the content access application 179 may access various other networkcontent served up by the computing environment 103 and/or other servers,thereby rendering a user interface 112 on the display 177. The contentaccess application 179 may provide various media player functionalityincluding, for example, initiating playback, stopping playback, pausingplayback, adjusting volume, setting preferences, browsing for mediacontent, searching for media content, recommending media content byrendering recommendations 115 (FIG. 1A), and so on. The content accessapplication 179 may include various decoding components 183 anddecryption components 185 corresponding to logic that facilitatesplayback of content items. Where the content corresponds toapplications, the content access application 179 may facilitateprogressive download and execution of applications.

The predictive caching system 181 is executed to predict various contentitems that the user is likely to access and to cache content iteminitial portions 121 (FIG. 1A) and content item metadata 124 (FIG. 1A)in the predictive cache 118 to facilitate instantaneous use. Thepredictive caching system 181 may also initialize various decodingcomponents 183, decryption components 185, etc. for content items in thepredictive cache 118. The size of the predictive cache 118 may depend,for example, on user-configured parameters, the available data storagein the client 106, the bandwidth available to the client 106 over thenetwork 109, or on other factors. In various embodiments, the client 106may be configured to make predictive caching decisions or the computingenvironment 103 may be configured to make predictive caching decisions.

The client 106 may also include a secure data store 187 for storage ofdecryption keys 157 used in decrypting content items to which the userhas rights in the client 106. The secure data store 187 may comply withvarious rules regarding security for storage of DRM licenses. The securedata store 187 may have relatively limited storage space for decryptionkeys 157. In some cases, the limited storage space in the secure datastore 187 may in turn limit the size of the predictive cache 118. Thepredictive caching system 181 may be configured to install thedecryption keys 157 in the secure data store 187 which the correspondingcontent items are predictively cached. The client 106 may be configuredto execute applications beyond the content access application 179 andthe predictive caching system 181 such as, for example, browsers, mobileapplications, email applications, social networking applications, and/orother applications.

Next, a general description of the operation of the various componentsof the networked environment 100 is provided. To begin, users mayregister and interact with the content server 139 such that behaviorhistory 160 (e.g., consumption history, etc.), bandwidth history 164,content preferences 166, watch lists 168, and/or other data in the useraccount data 148 is created for a content access account. Therecommendations engine 136 may process this data in order to generatethe recommended lists 170 for the users. In some cases, the recommendedlists 170 may be based on real-time behavior data 162 associated withthe users. Such real-time behavior data 162 may, for example, describe alisting of content items being presented to the user a user interface, alisting of search results generated in response to a search queryobtained from the user, and so on. The recommended lists 170 may dependfurther on the time of day, the day of the week, which subaccount isactive, etc.

The recommended lists 170 and/or other data used to generaterecommendations may be sent to the client 106 as recommendations data142. From a list of recommended content items, the predictive cachingsystem 181 selects a subset of the list based at least in part on arespective priority of the content items, an available data storage forthe client 106, available storage in the secure data store 187,available bandwidth, power state in the client 106, costs associatedwith the network 109 connection to the client 106, type of network 109connection to the client 106, configuration parameters, and/or otherfactors. In one embodiment, the predictive caching system 181 determinesthe selected subset according to a directive from the computingenvironment 103.

The predictive caching system 181 proceeds to predictively cache thecontent items in the selected subset. In doing so, the predictivecaching system 181 may prepare the client 106 for instantaneous use orplayback of the selected subset of content items before the user selectsany of the selected subset of content items for use. To this end, thepredictive caching system 181 may obtain initial portions from thecontent portions 153 and metadata such as manifests 155 and decryptionkeys 157 from the content server 139.

The content portions 153 may be sent in a decrypted format. To handlethis, the predictive caching system 181 may obtain decryption keys 157,which are then installed in the secure data store 187 to handle thedecryption. The predictive caching system 181 may spin up and initializehardware and/or software resources of the client 106, to include, forexample, decoding components 183, decryption components 185, and othercomponents of the content access application 179. Thus, the predictivecaching system 181 may perform some processing relative to the metadataand/or the initial portion of the content item in order to prepare theclient 106 for instantaneous playback of the predictively cached contentitems prior to the user explicitly indicating that use or playback isdesired.

Instantaneously available use may then be provided by the content accessapplication 179 when any of the selected subset of content items isselected for use or playback by the user. The content access application179 is configured to stream the selected content item from the contentserver 139 as a content stream 130. Although described as“instantaneous” playback, it is understood that such playback mayinclude a fade transition or other transition in order to avoid ajarring experience of cutting directly to playback.

Referring next to FIG. 2, shown is a flowchart that provides one exampleof the operation of a portion of the predictive caching system 181according to various embodiments. It is understood that the flowchart ofFIG. 2 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the predictive caching system 181 as described herein.As an alternative, the flowchart of FIG. 2 may be viewed as depicting anexample of steps of a method implemented in the client 106 (FIGS. 1A &1B) according to one or more embodiments.

Beginning with box 203, the predictive caching system 181 determines alist of recommended content items. To this end, the predictive cachingsystem 181 may obtain recommendations data 142 (FIG. 1B) from thecomputing environment 103 (FIG. 1B). Such recommendations data 142 maybe generated based at least in part on, for example, behavior history160 (FIG. 1B) including content consumption history, content preferences166 (FIG. 1B), real-time behavior data 162 (FIG. 1B), and/or other data.In some embodiments, the predictive caching system 181 may generate atleast a part of the list of recommended content items from real-timebehavior data 162 available in the client 106. The list of recommendedcontent items may have a priority associated with each content item inthe list. Such a priority may indicate a relative likelihood that theuser will want to consume the particular content item.

In box 206, the predictive caching system 181 selects a subset of thelist of recommended content items to be predictively cached. Theselection may be driven by priority of the respective content items,available resources in the client 106 (e.g., available memory or datastorage allocated for the predictive cache 118 (FIGS. 1A & 1B),available storage in the secure data store 187 (FIG. 1B), availablebandwidth on the network 109 (FIGS. 1A & 1B) for the client 106,bandwidth history 164 (FIG. 1B), content preferences 166 (FIG. 1B),real-time behavior data 162 available to the client 106, configurationparameters, and/or other factors.

In box 209, the predictive caching system 181 determines whetherpreviously cached content from the predictive cache 118 is to be purged.Such content may be purged in order to free up resources for othercontent that is determined to be more likely to be consumed by the user.The previously cached content may also be rendered obsolete by a changeto the factors which prompted its initial selection to be predictivelycached, e.g., if the content is no longer timely, if the real-timebehavior of the user that prompted the predictive caching of the contenthas changed, if the user has completed consuming the content, and so on.In some cases, the user may explicitly request that content be purgedfrom the cache.

If previously cached content is to be purged, the predictive cachingsystem 181 moves from box 209 to box 212 and determines which of thepreviously cached content items are to be purged. In some cases, theuser may explicitly identify which content is to be purged. In box 215,the predictive caching system 181 deallocates resources in the client106 that had been allocated to the content items that are to be purged.In doing so, the predictive caching system 181 may, for example, removecontent item initial portions 121 (FIG. 1A) from the predictive cache118, remove content item metadata 124 (FIG. 1A) from the predictivecache 118, remove unnecessary decryption keys 157 (FIG. 1B) from thesecure data store 187, terminate unnecessary decoding components 183(FIG. 1B) or decryption components 185 (FIG. 1B), and so on. Thepredictive caching system 181 then proceeds to box 218. If thepredictive caching system 181 instead decides not to purge previouslycached content, the predictive caching system 181 moves from box 209 tobox 218.

In box 218, the predictive caching system 181 obtains content iteminitial portions 121 from the content server 139 (FIG. 1B) for thecontent items that are to be predictively cached. The initial portionsmay correspond to the beginning of the content item, a location wherethe user left off in consuming the content item, a popular locationwithin the content item, and/or other starting portions within thecontent item. In box 221, the predictive caching system 181 obtainscontent item metadata 124 for the content items that are to bepredictively cached. Such content item metadata 124 may include, forexample, manifests 155 (FIG. 1B), decryption keys 157, and/or othermetadata. In box 224, the predictive caching system 181 initializesvarious components in the client 106 to facilitate instantaneous use orplayback of the predictively cached content items. This may include, forexample, launching and/or initializing decoding components 183 and/ordecryption components 185, storing decryption keys 157 in the securedata store 187, and/or performing other tasks.

In box 227, the predictive caching system 181 may render a userinterface 112 (FIGS. 1A & 1B) to present recommendations 115 (FIG. 1A)of predictively cached content items. By recommending such predictivelycached content items, the likelihood that the user will select contentthat has been predictively cached may be increased, thereby increasingthe likelihood of a positive user experience resulting frominstantaneous use. Thereafter, the portion of the predictive cachingsystem 181 ends.

Turning now to FIG. 3, shown is a flowchart that provides one example ofthe operation of a portion of the content access application 179according to various embodiments. It is understood that the flowchart ofFIG. 3 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the content access application 179 as describedherein. As an alternative, the flowchart of FIG. 3 may be viewed asdepicting an example of steps of a method implemented in the client 106(FIGS. 1A & 1B) according to one or more embodiments.

Beginning with box 303, the content access application 179 obtains arequest to use a content item. For instance, a user may navigate to auser interface 112 (FIGS. 1A & 1B) that presents a content item, and theuser may select a “play” button or other similar user interfacecomponent. In box 306, the content access application 179 determineswhether the content item has been predictively cached in the client 106.If the content item has not been predictively cached in the client 106,or if the predictive caching is incomplete, the content accessapplication 179 may continue to box 309.

In box 309, the content access application 179 obtains a content iteminitial portion 121 (FIG. 1A) from the content server 139 (FIG. 1B). Inbox 312, the content access application 179 obtains content itemmetadata 124 (FIG. 1A) from the content server 139. Such content itemmetadata 124 may include, for example, manifests 155 (FIG. 1B),decryption keys 157 (FIG. 1B), and/or other metadata. In box 315, thecontent access application 179 initializes various components in theclient 106 to facilitate use of the content items. This may include, forexample, launching and/or initializing decoding components 183 and/ordecryption components 185, storing decryption keys 157 in the securedata store 187, and/or performing other tasks.

It is noted that performing the tasks of boxes 309-315 may delayplayback of the content item relative to the case in which the contentitem has been predictively cached. The content access application 179then continues to box 318. If the content access application 179determines that the content item has been predictively cached, thecontent access application 179 moves from box 306 to box 318.

In box 318, the content access application 179 begins use of the contentitem. If the content item was predictively cached, an instantaneous useexperience is provided as the delay-inducing tasks of boxes 309-315 wereperformed in advance. In box 321, the content access application 179determines whether more data for the content item remains to be streamedor downloaded. If no more data remains, the portion of the contentaccess application 179 ends. If use is not finished, the content accessapplication 179 instead continues to box 324 and obtains a content itemsubsequent portion 127 (FIG. 1A) from the content server 139. Thecontent item subsequent portion 127 may be identified through processingthe manifest 155 for the content item. In box 327, the content accessapplication 179 plays back the content item subsequent portion 127. Thecontent access application 179 then returns to box 321 and determinesagain whether more data remains to be streamed or downloaded.

Moving on to FIG. 4, shown is a flowchart that provides one example ofthe operation of a portion of the content server 139 (FIGS. 1A & 1B)according to various embodiments. It is understood that the flowchart ofFIG. 4 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the content server 139 as described herein. As analternative, the flowchart of FIG. 4 may be viewed as depicting anexample of steps of a method implemented in the computing environment103 (FIGS. 1A & 1B) according to one or more embodiments.

Beginning with box 403, the content server 139 authenticates a user at aclient 106 (FIGS. 1A & 1B). In some cases, the user may be associatedwith a subaccount. The authentication may be performed by a cookie, by ausername/password combination, and/or by another security credential. Inbox 406, the content server 139 provides recommendations data 142 (FIG.1B) to the client 106. In some cases, the content server 139 may providedirectives to the client 106 to predictively cache certain contentitems. In box 409, the content server 139 obtains a request for contentdata 145 (FIG. 1B) from the client 106. The request may be for contentportions 153 (FIG. 1B), manifests 155 (FIG. 1B), decryption keys 157(FIG. 1B), and/or other content data 145.

In box 412, the content server 139 determines whether the client 106 hasrights to the content item to which the content data 145 pertains. Ifnot, the content server 139 may prompt the user to acquire the rights inbox 415. For example, the content server 139 may send data encoding auser interface 112 (FIGS. 1A & 1B) to the client 106, where the userinterface 112 prompts the user to purchase the content item or asubscription. Thereafter, the portion of the content server 139 ends. Insome cases, the encrypted content portions 153 and manifests 155 may besent to the client 106 without the decryption key 157 if the client 106does not have the rights.

If the client 106 does have the rights, the content server 139 movesfrom box 412 to box 418 and sends the content data 145 to the client 106over the network 109 (FIGS. 1A & 1B). In some cases, the content server139 may select from multiple bitrates for the content portions 153,multiple languages in the content portions 153, and/or otheralternatives based on data such as bandwidth history 164 (FIG. 1B),content preferences 166 (FIG. 1B), etc. The bitrate may be adaptivebased at least in part on the currently available bandwidth for theclient 106. In box 421, the content server 139 update the behaviorhistory 160 (FIG. 1B), the bandwidth history 164 (FIG. 1B), and/or otherdata. Thereafter, the portion of the content server 139 ends.

With reference to FIG. 5, shown is a schematic block diagram of thecomputing environment 103 according to an embodiment of the presentdisclosure. The computing environment 103 includes one or more computingdevices 500. Each computing device 500 includes at least one processorcircuit, for example, having a processor 503 and a memory 506, both ofwhich are coupled to a local interface 509. To this end, each computingdevice 500 may comprise, for example, at least one server computer orlike device. The local interface 509 may comprise, for example, a databus with an accompanying address/control bus or other bus structure ascan be appreciated.

Stored in the memory 506 are both data and several components that areexecutable by the processor 503. In particular, stored in the memory 506and executable by the processor 503 are the recommendations engine 136,the content server 139, and potentially other applications. Also storedin the memory 506 may be a data store 133 and other data. In addition,an operating system may be stored in the memory 506 and executable bythe processor 503. The client 106 (FIGS. 1A & 1B) may correspond to asimilar computing device 500 having a processor 503 and memory 506.

It is understood that there may be other applications that are stored inthe memory 506 and are executable by the processor 503 as can beappreciated. Where any component discussed herein is implemented in theform of software, any one of a number of programming languages may beemployed such as, for example, C, C++, C#, Objective C, Java®,JavaScript®, Perl, PHP, Visual Basic®, Python®, Ruby, Flash®, or otherprogramming languages.

A number of software components are stored in the memory 506 and areexecutable by the processor 503. In this respect, the term “executable”means a program file that is in a form that can ultimately be run by theprocessor 503. Examples of executable programs may be, for example, acompiled program that can be translated into machine code in a formatthat can be loaded into a random access portion of the memory 506 andrun by the processor 503, source code that may be expressed in properformat such as object code that is capable of being loaded into a randomaccess portion of the memory 506 and executed by the processor 503, orsource code that may be interpreted by another executable program togenerate instructions in a random access portion of the memory 506 to beexecuted by the processor 503, etc. An executable program may be storedin any portion or component of the memory 506 including, for example,random access memory (RAM), read-only memory (ROM), hard drive,solid-state drive, USB flash drive, memory card, optical disc such ascompact disc (CD) or digital versatile disc (DVD), floppy disk, magnetictape, or other memory components.

The memory 506 is defined herein as including both volatile andnonvolatile memory and data storage components. Volatile components arethose that do not retain data values upon loss of power. Nonvolatilecomponents are those that retain data upon a loss of power. Thus, thememory 506 may comprise, for example, random access memory (RAM),read-only memory (ROM), hard disk drives, solid-state drives, USB flashdrives, memory cards accessed via a memory card reader, floppy disksaccessed via an associated floppy disk drive, optical discs accessed viaan optical disc drive, magnetic tapes accessed via an appropriate tapedrive, and/or other memory components, or a combination of any two ormore of these memory components. In addition, the RAM may comprise, forexample, static random access memory (SRAM), dynamic random accessmemory (DRAM), or magnetic random access memory (MRAM) and other suchdevices. The ROM may comprise, for example, a programmable read-onlymemory (PROM), an erasable programmable read-only memory (EPROM), anelectrically erasable programmable read-only memory (EEPROM), or otherlike memory device.

Also, the processor 503 may represent multiple processors 503 and/ormultiple processor cores and the memory 506 may represent multiplememories 506 that operate in parallel processing circuits, respectively.In such a case, the local interface 509 may be an appropriate networkthat facilitates communication between any two of the multipleprocessors 503, between any processor 503 and any of the memories 506,or between any two of the memories 506, etc. The local interface 509 maycomprise additional systems designed to coordinate this communication,including, for example, performing load balancing. The processor 503 maybe of electrical or of some other available construction.

Although the recommendations engine 136, the content server 139, thecontent access application 179 (FIG. 1B), the predictive caching system181 (FIG. 1B), and other various systems described herein may beembodied in software or code executed by general purpose hardware asdiscussed above, as an alternative the same may also be embodied indedicated hardware or a combination of software/general purpose hardwareand dedicated hardware. If embodied in dedicated hardware, each can beimplemented as a circuit or state machine that employs any one of or acombination of a number of technologies. These technologies may include,but are not limited to, discrete logic circuits having logic gates forimplementing various logic functions upon an application of one or moredata signals, application specific integrated circuits (ASICs) havingappropriate logic gates, field-programmable gate arrays (FPGAs), orother components, etc. Such technologies are generally well known bythose skilled in the art and, consequently, are not described in detailherein.

The flowcharts of FIGS. 2-4 show the functionality and operation of animplementation of portions of the predictive caching system 181, thecontent access application 179, and the content server 139. If embodiedin software, each block may represent a module, segment, or portion ofcode that comprises program instructions to implement the specifiedlogical function(s). The program instructions may be embodied in theform of source code that comprises human-readable statements written ina programming language or machine code that comprises numericalinstructions recognizable by a suitable execution system such as aprocessor 503 in a computer system or other system. The machine code maybe converted from the source code, etc. If embodied in hardware, eachblock may represent a circuit or a number of interconnected circuits toimplement the specified logical function(s).

Although the flowcharts of FIGS. 2-4 show a specific order of execution,it is understood that the order of execution may differ from that whichis depicted. For example, the order of execution of two or more blocksmay be scrambled relative to the order shown. Also, two or more blocksshown in succession in FIGS. 2-4 may be executed concurrently or withpartial concurrence. Further, in some embodiments, one or more of theblocks shown in FIGS. 2-4 may be skipped or omitted. In addition, anynumber of counters, state variables, warning semaphores, or messagesmight be added to the logical flow described herein, for purposes ofenhanced utility, accounting, performance measurement, or providingtroubleshooting aids, etc. It is understood that all such variations arewithin the scope of the present disclosure.

Also, any logic or application described herein, including therecommendations engine 136, the content server 139, the content accessapplication 179, and the predictive caching system 181, that comprisessoftware or code can be embodied in any non-transitory computer-readablemedium for use by or in connection with an instruction execution systemsuch as, for example, a processor 503 in a computer system or othersystem. In this sense, the logic may comprise, for example, statementsincluding instructions and declarations that can be fetched from thecomputer-readable medium and executed by the instruction executionsystem. In the context of the present disclosure, a “computer-readablemedium” can be any medium that can contain, store, or maintain the logicor application described herein for use by or in connection with theinstruction execution system.

The computer-readable medium can comprise any one of many physical mediasuch as, for example, magnetic, optical, or semiconductor media. Morespecific examples of a suitable computer-readable medium would include,but are not limited to, magnetic tapes, magnetic floppy diskettes,magnetic hard drives, memory cards, solid-state drives, USB flashdrives, or optical discs. Also, the computer-readable medium may be arandom access memory (RAM) including, for example, static random accessmemory (SRAM) and dynamic random access memory (DRAM), or magneticrandom access memory (MRAM). In addition, the computer-readable mediummay be a read-only memory (ROM), a programmable read-only memory (PROM),an erasable programmable read-only memory (EPROM), an electricallyerasable programmable read-only memory (EEPROM), or other type of memorydevice.

It should be emphasized that the above-described embodiments of thepresent disclosure are merely possible examples of implementations setforth for a clear understanding of the principles of the disclosure.Many variations and modifications may be made to the above-describedembodiment(s) without departing substantially from the spirit andprinciples of the disclosure. All such modifications and variations areintended to be included herein within the scope of this disclosure andprotected by the following claims.

Therefore, the following is claimed:
 1. A system, comprising: at leastone computing device; and a predictive caching system executable in theat least one computing device, wherein when executed the predictivecaching system causes the at least one computing device to at least:determine a recommended content item; send metadata associated with therecommended content item from to a client prior to an indication fromthe client that use of the recommended content item is desired; andcause processing relative to the metadata to be performed in the clientto prepare the client for playback of the recommended content item priorto the indication from the client that use of the recommended contentitem is desired.
 2. The system of claim 1, wherein the recommendedcontent item is selected from a set of recommended content itemsaccording to a relative priority.
 3. The system of claim 1, wherein theprocessing relative to the metadata further comprises initializing adecryption component in the client for decrypting an initial portion ofthe recommended content item.
 4. The system of claim 1, wherein theprocessing relative to the metadata further comprises initializing adecoding component in the client for decoding an initial portion of therecommended content item.
 5. The system of claim 1, wherein therecommended content item is determined based at least in part on a mediaconsumption history of a user associated with the client.
 6. The systemof claim 1, wherein the recommended content item is determined based atleast in part on real-time behavior data of a user associated with theclient, the real-time behavior data indicating at least one of: contentcurrently browsed by a user, a search query currently executed by theuser, or a search result currently being displayed to the user.
 7. Thesystem of claim 1, wherein when executed the predictive caching systemfurther causes the at least one computing device to at least send aninitial portion of the recommended content item to the client prior tothe indication from the client that use of the recommended content itemis desired.
 8. The system of claim 1, wherein the metadata comprises amanifest file that includes sequence-specifying data and respectiveidentifiers for a plurality of portions of the recommended content item.9. The system of claim 1, wherein the metadata comprises a decryptionkey for decrypting an encrypted initial portion of the recommendedcontent item.
 10. The system of claim 9, wherein the decryption key isconfigured to expire at a particular time or after a time period.
 11. Amethod, comprising: determining, by a computing device, a recommendedcontent item; determining that the computing device has availableresources to facilitate instantaneous use of the recommended contentitem; and in response to determining that the computing device hasavailable resources to facilitate instantaneous use of the recommendedcontent item and before use of the recommended content item: obtaining,by the computing device, metadata for the recommended content item froma server; and initializing, by the computing device, the availableresources to prepare for instantaneous use of the recommended contentitem based at least in part on the metadata.
 12. The method of claim 11,further comprising rendering, by the computing device, a recommendationfor the recommended content item in a user interface after the availableresources are initialized to prepare for instantaneous use of therecommended content item.
 13. The method of claim 11, further comprisingobtaining, by the computing device, respective portions of therecommended content item in a plurality of bitrates from the server. 14.The method of claim 11, further comprising obtaining, by the computingdevice, respective portions of the recommended content item in aplurality of languages from the server.
 15. The method of claim 11,wherein the available resources comprise a network bandwidth currentlyavailable to the computing device.
 16. A method, comprising:determining, by at least one computing device, a set of recommendedmedia content items for a client; preparing, by the at least onecomputing device, the client for instantaneous playback of the set ofrecommended media content items before a selection of any of the set ofrecommended media content items for playback; and performing, by the atleast one computing device, processing of a first recommended mediacontent item of the set of recommended media content items in responseto the first recommended media content item being selected for playbackafter the client is prepared for instantaneous playback of the firstrecommended media content item.
 17. The method of claim 16, whereinpreparing the client for instantaneous playback of the set ofrecommended media content items further comprises: obtaining, by thecomputing device, metadata for individual ones of the set of recommendedcontent items from a server; and performing, by the computing device,processing relative to the metadata.
 18. The method of claim 16, whereinthe set of recommended content items is determined based at least inpart on real-time behavior data of the client.
 19. The method of claim16, wherein the set of recommended content items is determined based atleast in part on a media consumption history of the client.
 20. Themethod of claim 16, wherein the set of recommended content items isdetermined based at least in part on an amount of available resources inthe client.